A structural Gaussian mixture vector autoregressive model is introduced. The shocks are identified by combining simultaneous diagonalization of the reduced form error covariance matrices with constraints on the time-varying impact matrix. This leads to flexible identification conditions, and some of the constraints are also testable. The empirical application studies asymmetries in the effects of the U.S. monetary policy shock and finds strong asymmetries with respect to the sign and size of the shock and to the initial state of the economy. The accompanying CRAN distributed R package gmvarkit provides a comprehensive set of tools for numerical analysis.

翻译：引入了高斯的结构性混合物矢量自动递减模型,通过同时对形式差错共变矩阵进行对齐和对时间变化影响矩阵的限制来识别冲击。这导致灵活的识别条件,一些限制也可以测试。实验应用研究美国货币政策冲击效应的不对称性,并发现在冲击信号和大小以及初始经济状态方面存在着强烈的不对称性。伴随的CRAN分发的R包 Gmvarkit提供了一套全面的数值分析工具。